Phyllis Wan

Welcome!

I am an Assistant Professor in Statistics at the Erasmus School of Economics, Erasmus University Rotterdam.

My research interest lies in the study of complex data structures, such as networks and time series. I am especially interested in scenarios where heavy-tailed observations are present and where novel statistical tools are called for!

I obtained my PhD from the Department of Statistics at Columbia University, under the supervision of Prof. Richard Davis.

Contact

Erasmus School of Economics, H11-22

Erasmus University Rotterdam

P.O. Box 1738

3000DR Rotterdam, the Netherlands

wan at ese.eur.nl

Papers

  • An extreme value analysis of the urban skyline (2018+), with Auerbach, J.L. [arXiv, press]
  • Are extreme value estimation methods useful for network data? (2018+), with Wang, T., Davis, R.A. and Resnick, S.I. [arXiv]
  • Threshold selection for multivariate heavy-tailed data (2018+), with Davis, R.A., in Extremes. [link, arXiv]
  • Applications of distance covariance to time series (2018), with Davis, R.A., Matsui, M. and Mikosch, T., in Bernoulli. [link, arXiv]
  • Fitting the linear preferential attachment model (2017), with Wang, T., Davis, R.A. and Resnick, S.I., in Electronic Journal of Statistics. [link, arXiv]
  • Nonstandard regular variation of in-degree and out-degree in the preferential attachment model (2016), with Samorodnitsky, G., Resnick, S.I., Towsley, D., Davis, R.A. and Willis, A., in Journal of Applied Probability. [link, arXiv]

Google Scholar profile

List of presentations

Teaching

  • Course Instructor
    • STAT 1111: Introduction to Statistics w/o Calculus
    • Review for Theoretical Statistics PhD Qualification Exam
  • Teaching Assistant
    • STAT 1211: Introduction to Statistics w/ Calculus
    • STAT 3105: Probability
    • STAT 3106: Applied Data Mining
    • STAT 3107: Statistical Inference
    • STAT 4240: Data Mining
    • STAT 4260: Bayesian Statistics
    • STAT 4400: Statistical Machine Learning
    • STAT 4437: Time Series Analysis
    • STAT 4701: Statistical Inference and Modeling
    • STAT 6301: Probability, PhD level